Many imaging applications involve generating a sequence of two-dimensional (2D) or three-dimensional (3D) images representing a particular object of interest in respective time intervals. Examples include a wide variety of well-known medical imaging applications such as magnetic-resonance imaging (MRI), positron emission tomography (PET) and computed tomography (CT). The image sequences generated in these and other imaging applications are also commonly referred to as spatio-temporal images, in that the image data varies both in the spatial domain, that is, within each of the individual 2D or 3D images, as well as in the temporal domain, that is, from time interval to time interval.
In a typical arrangement, raw data is captured by a scanner as a series of frames, with each frame corresponding to a time interval. The captured data for each frame is processed to reconstruct a spatial image representing the state of the object in the corresponding time interval. The image reconstruction process may be formulated as a mathematical optimization problem based on a physical model characterizing data capture by the scanner. Spatial images are usually reconstructed individually on a frame-by-frame basis, and these spatial images are then aggregated together to provide the spatio-temporal image.
In situations involving imaging of repetitive phenomena such as heart beat or respiration, raw data is often captured for multiple cycles of repetition, using so-called “gated” arrangements. Each cycle of repetition is subdivided into multiple frames, with each frame of a given cycle representing a corresponding time interval in that cycle. Spatial images are reconstructed independently for each time interval using the frames associated with that time interval, which would include one frame from each of the multiple cycles. Again, these spatial images are then aggregated together to provide the spatio-temporal image.
There is an inherent tradeoff between spatial resolution and temporal resolution in arrangements such as those described above. For example, one can attempt to improve the temporal resolution by increasing the number of frames captured within a given time period, but this will decrease the amount of data captured in each frame, leading to a poorer spatial resolution. Also, it is often desirable to limit the scan time as certain of the medical imaging applications may involve exposing a patient to significant levels of potentially harmful radiation.